the objective: For every board item, the lowest altitude that can do it (the least power that suffices); starts the loops; commits the result
cuts 51 board items into 3 slices
sha256:e94c2ec3533ba2f017 items · 24 LLM calls, until each answer is valid, then stop
sha256:91d86c813cdf7ab917 items · 28 LLM calls, until each answer is valid, then stop
sha256:c9cc52812d792d1217 items · 29 LLM calls, until each answer is valid, then stop
sha256:f45602b48a8abc9bopen weight (deepseek/deepseek-v4-flash), no tools · 33 retried · 0.003394 USD · 81 keys, one per call
verifies all 85 signatures: all valid; merges
sha256:cc31d3b2529f341b51 items, 3 with no valid answer in three calls; 33 of 81 calls retried. A model's placement is evidence, not a decision. What it teaches: our board items are whole projects, each mixing altitudes; route work after cutting it into loops and calls, not before.
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